In today's business and scientific world, color has become essential as a component of communication. Color facilitates the sharing of knowledge and ideas. Companies involved in the development of digital color print engines are continuously looking for ways to improve the total image quality of their products. One of the elements that affects image quality is the ability to consistently produce the same quality image output on a printer from one day to another, from one week to the next, month after month. Users have become accustomed to printers and copiers that produce high quality color and gray-scaled output. Users now expect to be able to reproduce a color image with consistent quality on any compatible marking device, including another device within an organization, a device at home or a device used anywhere else in the world. There has been a long felt commercial need for efficiently maintaining print color predictability, particularly as electronic marketing has placed more importance on the accurate representation of merchandise in illustrative print or display media.
Description of color, color perception and psychological and physiological phenomena involving light, object and observer, including color measurements using spectrophotometers are described in R. W. G. Hunt, “The Reproduction of Color in Photography, Printing and Television”. Fourth Edition, Fountain Press, Tolworth, England 1987 ISBN 0-8524-2356.
The functional models presented in this specification use a device independent color space to consistently track a set of target colors. L*, a*, b* are the CIE (Commission Internationale de L'eclairage) color standards utilized in the modeling. L* defines lightness, a* corresponds to the red/green value and b* denotes the amount of yellow/blue, which corresponds to the way people perceive color. A neutral color is a color where a*=b*=0.
Over time, the output of conventional marking devices drift (or deviate from predetermined optimum standards) due to various factors. These factors include environmental conditions (temperature, relative humidity, etc.), the type of media (e.g., different paper types and paper batches, transparencies, etc.) used, variations in media, variations from original models used in initialization, general wear, etc. When a marking device is originally initialized, and at regular or irregular intervals thereafter, it is calibrated and characterized to produce output as close as possible to a reference standard. The full calibration and characterization process, however, is time consuming and expensive, particularly because specific expertise is required.
As an example, calibration and characterization of a conventional four-color CMYK (cyan, magenta, yellow and black) printer or copier involves at least the following processes: (1) generating a 3D look-up table (LUT) for mapping device independent parameter space to CMY (cyan-magenta-yellow) space; (2) executing a GCR (gray component replacement)/UCR (under color removal) strategy to convert the CMY space parameters to CMYK space parameters which represent the colors of a typical four-color marking device; (3) constructing marking device TRCs (tone reproduction curves) to account for marking device variabilities (normally done at the time of manufacturing or whenever the printer calibration and characterization process is involved); and (4) applying a suitable half-toning strategy to convert the CMYK continuous tone description obtained after using the 3D LUTs in steps 1 and 2 above and 1 D LUTs in step 3 above, to the image. The first two steps are generally grouped under printer characterization. The third step is normally called calibration for the purpose of the subject invention. The hardware/software package for implementing these processes in a marking device is typically identified as the “digital front end” (DFE).
In processing the image, the critical step that accounts for variations in marking device output is TRC construction. TRCs are stored plots of an input parameter value versus an output parameter value for a particular color. A TRC is a monotonically increasing marking device function in input-output contone space or input-output density space or input-output byte space, or combinations thereof. In other words, a TRC indicates the value of the output parameter for a specific device that must be used to reproduce the input parameter (if the input and output parameters are exactly equal, then the inputs and outputs are expressed in the same coordinate space). Inaccuracies in the TRC construction step can lead to inaccuracies in color balancing and the 3D LUT. In modern printing systems such functional modeling can contain complex control and calibration loops. These loops measure the state of the image on the photoreceptor by measuring the charge and the developed mass and actuate the charging and development system parameters to maintain the developability to some target setpoints. Other level loops, on the other hand, are designed to produce the TRCs for each separation by measuring the developed toner mass on the photoreceptor belt. These process loops can maintain the developability of each separation to some target set points. However, a particular problem exists in that controlling developed mass on the belt alone will not give consistent color on the media because of variabilities in the transfer and media. Gray balanced calibration and profiling loops are expected to minimize the inconsistency on a single as well as multiple media. The gray balanced loops use the spectrophotometric measurements of the patches near neutral and produce one-dimensional TRCs as correction LUTs for the image. The profiling loops also use the spectrophotometric measurements, but are designed to produce a complex four-to-four or three-to-four multidimensional LUTs. Designing these colorimetric/photometric correction loops require accurate models. Phenomenological, Neugerbour models are currently used extensively in building one and multidimensional LUTs. Data on an exemplary printer shows that the Neugerbour models have a prediction mean error of deltaE=4 and max error of deltaE=9. Many times these errors are caused by non-uniformity in the printed area on the page. This leads to measurements errors. Further refinements in TRC modeling to get improved accuracy are difficult due to the measurement errors in the model.
A full-fledged printer characterization/profiling is costly and time consuming because colors have to be measured through out the color space and therefore can involve a large number of color test patches and iterations.
The subject invention is particularly useful to provide solutions to the foregoing color problems for a wide range of color workflow practices. Improved modeling can be used for controlling customer selectable colors, spot colors and constructing gray balanced LUTs and building profiles using inline/offline spectrophotometric measurements. Printing and product enhancements are provided that would enable customers to manipulate color documents on a screen before even printing/displaying an output on different output devices in ways that improve the productivity of a current workflow by taking advantages of more consistent and accurate output colors produced by the printing devices.
The subject invention exploits a key enabling factor for these operational advantages by utilizing state-space based methods that are increasingly useful due to the corresponding complexity in nature of the printing systems. First principle/phenomenological models will not give accurate color due to the need to fit too many parameters.